Prevalence effects in visual research: Theoretical and practical implications

视觉研究中的流行效应：理论和实践意义

• 批准号: 10181436
• 负责人: Jeremy M Wolfe
• 金额: $ 1.61万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-03-01 至 2022-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10181436
• 关键词: Behavior; Berry; Biological Models; Clinic; Clinical; Dangerousness; Detection; Failure; Goals; Grant; Home environment; Human; Hybrids; Incidental Findings; Influentials; Interruption; Intervention; Laboratories; Lead; Legal; Life; Literature; Low Prevalence; Malignant Neoplasms; Malignant neoplasm of lung; Medical; Medical Errors; Memory; Methods; Modeling; Ocimum basilicum; Patients; Performance; Pneumonia; Prevalence; Prevalence Study; Probability; Process; Radiology Specialty; Reporting; Research; Screening for cancer; Series; Signal Transduction; Stimulus; Structure; Supermarket; Testing; Time; Tomatoes; Vision research; Visual; Work; behavioral study; experimental study; improved; inattentional blindness; insight; interest; novel; programs; radiologist; rib bone structure; satisfaction; screening; social; tool; vigilance; visual memory; visual process; visual search

In medical exams, “incidental findings” are findings that should be noted but that are incidental to the purpose of the exam (e.g. looking for pneumonia and unexpectedly finding cancer). Missed incidental findings can have significant medical and legal consequences. These errors can be considered as “satisfaction of search” errors and are closely related to “inattentional blindness” in basic vision research. Such errors occur regularly in daily life, as when, after a search of the supermarket, you arrive home with the tomatoes, but not the basil. The goal of this proposal is to understand the conditions that produce incidental finding errors in socially-important search tasks and to use that understanding to generate interventions that can improve the efficiency of those searches and reduce failure rates. We will develop a laboratory model of incidental findings built on aspects of search behavior studied extensively in our lab in the prior grant period: First, we have studied “hybrid search” tasks in which observers search for multiple types of target at the same time, combining visual search and memory search. Second, we pioneered the study of human “foraging” search - search for an unknown numbers of instances of one target type (e.g. picking berries). Combining those two paradigms, we have studied “hybrid foraging” in which observers search for an unknown number of instances of multiple targets (analogous to some medical situations). Finally, we have extensively studied `prevalence effects'; the finding that rare items are found less successfully in search, simply as a function of their low prevalence. We have documented these prevalence effects in the lab, in baggage screening and in cancer screening. Building on this prior work, there are three specific aims: 1) We will combine hybrid search, foraging, and low prevalence methods into a model system to test the hypothesis that the structure of some clinical search tasks makes it more likely that incidental findings will be missed. We will compare our model system to radiologists' behavior and we will assess interventions to reduce these false negative errors. 2) We will use a second model system to study the impact of vigilance/time-on-task and interruption. Here we use signal detection methods to distinguish changes in detectability from criterion shifts. 3) Our Guided Search (GS) model has been a leading account of search performance in classic search tasks. The third aim is to have a GS model that can predict conditions that will produce high rates of incidental finding errors. More importantly, the model will be a tool that can be used to identify testable conditions that might minimize those errors. Our experiments will provide insights into fundamental processes of visual search and can lead to interventions that can be used to reduce a dangerous type of medical error.

在医学检查中，“偶然发现”是指应注意但偶然发生的发现。 检查的目的（例如寻找肺炎和意外发现癌症）。偶然错过 研究结果可能会产生重大的医学和法律后果。这些错误可以被认为是 “搜索满意度”错误与基本视力的“无意盲视”密切相关 研究。此类错误在日常生活中经常发生，例如，在搜索完超市后，您 带着西红柿回家，但没有罗勒。该提案的目标是了解 在具有社会重要性的搜索任务中产生偶然发现错误的条件并使用它 了解产生干预措施，可以提高这些搜索的效率并减少 故障率。我们将开发一个基于搜索方面的偶然发现的实验室模型 在之前的资助期内，我们的实验室对行为进行了广泛的研究：首先，我们研究了“混合搜索” 观察者同时搜索多种类型目标的任务，结合视觉搜索 和记忆搜索。其次，我们开创了人类“觅食”搜索的研究——寻找 一种目标类型的实例数量未知（例如采摘浆果）。结合这两者 范式中，我们研究了“混合觅食”，其中观察者寻找未知数量的 多个目标的实例（类似于某些医疗情况）。最后，我们广泛地 研究了“流行效应”；发现稀有物品在搜索中不太成功，简单地说 由于其患病率较低。我们已经在实验室中记录了这些患病率的影响 行李检查和癌症检查。基于之前的工作，我们实现了三个具体目标： 1）我们将混合搜索、觅食和低流行方法结合到模型系统中进行测试 假设某些临床搜索任务的结构更有可能是偶然的 结果将会被遗漏。我们将把我们的模型系统与放射科医生的行为进行比较，我们将 评估干预措施以减少这些假阴性错误。 2）我们将使用第二个模型系统来研究警惕性/任务时间和干扰的影响。 在这里，我们使用信号检测方法来区分可检测性的变化和标准变化。 3) 我们的引导搜索（GS）模型一直是经典搜索性能的领先指标 搜索任务。第三个目标是建立一个 GS 模型，可以预测将产生的条件 偶然发现错误的比率很高。更重要的是，模型将成为一个可以使用的工具 以确定可以最小化这些错误的可测试条件。 我们的实验将提供对视觉搜索基本过程的见解，并可能导致 可用于减少危险类型的医疗错误的干预措施。